| # DESCRIPTION OF THE DATASET |
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| This dataset was created for real-time fitness exercise classification and includes a diverse mix of synthetic and real-world videos. It focuses on four common exercises: |
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| - Squat |
| - Push-up |
| - Barbell Bicep Curl |
| - Shoulder Press |
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| # DEMO OF MY PROJECT THAT USED THIS DATASET (AI PERSONAL TRAINER): |
| [](https://www.youtube.com/watch?v=GPmDPB1bSmc) |
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| GITHUB PROJECT (with implementation): |
| https://github.com/RiccardoRiccio/Fitness-AI-Trainer-With-Automatic-Exercise-Recognition-and-Counting |
| The dataset was compiled from three main sources: |
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| 📁 Kaggle Workout/Exercises Video Dataset |
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| - Real-world videos of expert trainers performing various exercises |
| - Only four exercises were selected |
| - ~25 videos per class were curated, ensuring balanced representation |
| - Supplemented with additional online videos to increase variation in lighting, angle, and environment |
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| 🧍 InfiniteRep Dataset |
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| - Synthetic videos of human-like avatars performing exercises |
| - 100 videos per class selected |
| - Offers control over pose variation, camera angles etc. |
| - Enhances model robustness and dataset size |
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| 🌐 Additional Online Videos |
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| - Sourced from Pexels, Pixabay, Shutterstock, etc. |
| - Added to reflect how users might perform exercises in home or gym environments |
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| # Remember to upvote the dataset! |
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| license: cc-by-nc-sa-4.0 |
| task_categories: |
| - video-classification |
| - image-classification |
| - image-segmentation |
| language: |
| - en |
| tags: |
| - gym |
| - exercise |
| - biology |
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